Nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images

Yong Yue; Mihai M. Croitoru; Akhil Bidani; Joseph B. Zwischenberger; John W. Clark

doi:10.1109/TMI.2005.862737

Nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images

Yong Yue, Mihai M. Croitoru, Akhil Bidani, Joseph B. Zwischenberger, John W. Clark

Research output: Contribution to journal › Article › peer-review

193 Scopus citations

Abstract

This paper introduces a novel nonlinear multiscale wavelet diffusion method for ultrasound speckle suppression and edge enhancement. This method is designed to utilize the favorable denoising properties of two frequently used techniques: the sparsity and multiresolution properties of the wavelet, and the iterative edge enhancement feature of nonlinear diffusion. With fully exploited knowledge of speckle image models, the edges of images are detected using normalized wavelet modulus. Relying on this feature, both the envelope-detected speckle image and the log-compressed ultrasonic image can be directly processed by the algorithm without need for additional preprocessing. Speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients. With a tuning diffusion threshold strategy, the proposed method can improve the image quality for both visualization and auto-segmentation applications. We validate our method using synthetic speckle images and real ultrasonic images. Performance improvement over other despeckling filters is quantified in terms of noise suppression and edge preservation indices.

Original language	English
Pages (from-to)	297-311
Number of pages	15
Journal	IEEE Transactions on Medical Imaging
Volume	25
Issue number	3
DOIs	https://doi.org/10.1109/TMI.2005.862737
State	Published - Mar 2006

Bibliographical note

Funding Information:
Manuscript received Aug. 25, 2005; revised November 22, 2005. This work was supported in part by the Biomedical Engineering Center, University of Texas Medical Branch, Galveston, TX. Asterisk indicates corresponding author. Y. Yue is with Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005 USA (e-mail: yyue@rice.edu). M. M. Croitoru and A. Bidani are with University of Texas Medical School at Houston, Houston TX 77030 USA. J. B. Zwischenberger is with University of Texas Medical Branch, Galveston, TX 77555 USA. *J. W. Clark, Jr. is with Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005 USA (e-mail: jwc@rice.edu). Digital Object Identifier 10.1109/TMI.2005.862737

Keywords

Dyadic wavelet transform
Iterative denoising
Multiscale analysis
Nonlinear diffusion
Speckle suppression
Ultrasound imaging
Wavelet diffusion. © 2006 ieee

ASJC Scopus subject areas

Software
Radiological and Ultrasound Technology
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TMI.2005.862737

Cite this

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title = "Nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images",

abstract = "This paper introduces a novel nonlinear multiscale wavelet diffusion method for ultrasound speckle suppression and edge enhancement. This method is designed to utilize the favorable denoising properties of two frequently used techniques: the sparsity and multiresolution properties of the wavelet, and the iterative edge enhancement feature of nonlinear diffusion. With fully exploited knowledge of speckle image models, the edges of images are detected using normalized wavelet modulus. Relying on this feature, both the envelope-detected speckle image and the log-compressed ultrasonic image can be directly processed by the algorithm without need for additional preprocessing. Speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients. With a tuning diffusion threshold strategy, the proposed method can improve the image quality for both visualization and auto-segmentation applications. We validate our method using synthetic speckle images and real ultrasonic images. Performance improvement over other despeckling filters is quantified in terms of noise suppression and edge preservation indices.",

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note = "Funding Information: Manuscript received Aug. 25, 2005; revised November 22, 2005. This work was supported in part by the Biomedical Engineering Center, University of Texas Medical Branch, Galveston, TX. Asterisk indicates corresponding author. Y. Yue is with Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005 USA (e-mail: yyue@rice.edu). M. M. Croitoru and A. Bidani are with University of Texas Medical School at Houston, Houston TX 77030 USA. J. B. Zwischenberger is with University of Texas Medical Branch, Galveston, TX 77555 USA. *J. W. Clark, Jr. is with Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005 USA (e-mail: jwc@rice.edu). Digital Object Identifier 10.1109/TMI.2005.862737",

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N2 - This paper introduces a novel nonlinear multiscale wavelet diffusion method for ultrasound speckle suppression and edge enhancement. This method is designed to utilize the favorable denoising properties of two frequently used techniques: the sparsity and multiresolution properties of the wavelet, and the iterative edge enhancement feature of nonlinear diffusion. With fully exploited knowledge of speckle image models, the edges of images are detected using normalized wavelet modulus. Relying on this feature, both the envelope-detected speckle image and the log-compressed ultrasonic image can be directly processed by the algorithm without need for additional preprocessing. Speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients. With a tuning diffusion threshold strategy, the proposed method can improve the image quality for both visualization and auto-segmentation applications. We validate our method using synthetic speckle images and real ultrasonic images. Performance improvement over other despeckling filters is quantified in terms of noise suppression and edge preservation indices.

AB - This paper introduces a novel nonlinear multiscale wavelet diffusion method for ultrasound speckle suppression and edge enhancement. This method is designed to utilize the favorable denoising properties of two frequently used techniques: the sparsity and multiresolution properties of the wavelet, and the iterative edge enhancement feature of nonlinear diffusion. With fully exploited knowledge of speckle image models, the edges of images are detected using normalized wavelet modulus. Relying on this feature, both the envelope-detected speckle image and the log-compressed ultrasonic image can be directly processed by the algorithm without need for additional preprocessing. Speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients. With a tuning diffusion threshold strategy, the proposed method can improve the image quality for both visualization and auto-segmentation applications. We validate our method using synthetic speckle images and real ultrasonic images. Performance improvement over other despeckling filters is quantified in terms of noise suppression and edge preservation indices.

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Nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images

Abstract

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Keywords

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